Intent-Recognition-Based Traded Control for Telerobotic Assembly over High-Latency Telemetry

As we deploy robotic manipulation systems into unstructured real-world environments, the tasks which those robots are expected to perform grow very quickly in complexity. These tasks require a greater number of possible actions, more variable environmental conditions, and larger varieties of objects and materials which need to be manipulated. This in turn leads to a greater number of ways in which elements of a task can fail. When the cost of task failure is high, such as in the case of surgery or on-orbit robotic interventions, effective and efficient task recovery is essential. Despite ever-advancing capabilities, however, the current and near future state-of-the-art in fully autonomous robotic manipulation is still insufficient for many tasks in these critical applications. Thus, successful application of robotic manipulation in many application domains still necessitates a human operator to directly teleoperate the robots over some communications infrastructure. However, any such infrastructure always incurs some unavoidable round-trip telemetry latency depending on the distances involved and the type of remote environment. While direct teleoperation is appropriate when a human operator is physically close to the robots being controlled, there are still many applications in which such proximity is infeasible. In applications which require a robot to be far from its human operator, this latency can approach the speed of the relevant task dynamics, and performing the task with direct telemanipulation can become increasingly difficult, if not impossible. For example, round-trip delays for ground-controlled on-orbit robotic manipulation can reach multiple seconds depending on the infrastructure used and the location of the remote robot. The goal of this thesis is to advance the state-of-the art in semi-autonomous telemanipulation under multi-second round-trip communications latency between a human operator and remote robot in order to enable more telerobotic applications. We propose a new intent-recognition-based traded control (IRTC) approach which automatically infers operator intent and executes task elements which the human operator would otherwise be unable to perform. What makes our approach more powerful than the current approaches is that we prioritize preserving the operator's direct manual interaction with the remote environment while only trading control over to an autonomous subsystem when the operator-local intent recognition system automatically determines what the operator is trying to accomplish. This enables operators to perform unstructured and a priori unplanned actions in order to quickly recover from critical task failures. Furthermore, this thesis also describes a methodology for introducing and improving semi-autonomous control in critical applications. Specifically, this thesis reports (1) the demonstration of a prototype system for IRTC-based grasp assistance in the context of transatlantic telemetry delays, (2) the development of a systems framework for IRTC in semi-autonomous telemanipulation, and (3) an evaluation of the usability and efficacy of that framework with an increasingly complex assembly task. The results from our human subjects experiments show that, when incorporated with sufficient lower-level capabilities, IRTC is a promising approach to extend the reach and capabilities of on-orbit telerobotics and future in-space operations

Elevated AKR1C3 expression promotes prostate cancer cell survival and prostate cell-mediated endothelial cell tube formation: implications for prostate cancer progressioan

<p>Abstract</p> <p>Background</p> <p>Aldo-keto reductase (AKR) 1C family member 3 (AKR1C3), one of four identified human AKR1C enzymes, catalyzes steroid, prostaglandin, and xenobiotic metabolism. In the prostate, AKR1C3 is up-regulated in localized and advanced prostate adenocarcinoma, and is associated with prostate cancer (PCa) aggressiveness. Here we propose a novel pathological function of AKR1C3 in tumor angiogenesis and its potential role in promoting PCa progression.</p> <p>Methods</p> <p>To recapitulate elevated AKR1C3 expression in cancerous prostate, the human PCa PC-3 cell line was stably transfected with an AKR1C3 expression construct to establish PC3-AKR1C3 transfectants. Microarray and bioinformatics analysis were performed to identify AKR1C3-mediated pathways of activation and their potential biological consequences in PC-3 cells. Western blot analysis, reverse transcription-polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and an <it>in vitro </it>Matrigel angiogenesis assays were applied to validate the pro-angiogenic activity of PC3-AKR1C3 transfectants identified by bioinformatics analysis.</p> <p>Results</p> <p>Microarray and bioinformatics analysis suggested that overexpression of AKR1C3 in PC-3 cells modulates estrogen and androgen metabolism, activates insulin-like growth factor (IGF)-1 and Akt signaling pathways, as well as promotes tumor angiogenesis and aggressiveness. Levels of IGF-1 receptor (IGF-1R) and Akt activation as well as vascular endothelial growth factor (VEGF) expression and secretion were significantly elevated in PC3-AKR1C3 transfectants in comparison to PC3-mock transfectants. PC3-AKR1C3 transfectants also promoted endothelial cell (EC) tube formation on Matrigel as compared to the AKR1C3-negative parental PC-3 cells and PC3-mock transfectants. Pre-treatment of PC3-AKR1C3 transfectants with a selective IGF-1R kinase inhibitor (AG1024) or a non-selective phosphoinositide 3-kinases (PI3K) inhibitor (LY294002) abolished ability of the cells to promote EC tube formation.</p> <p>Conclusions</p> <p>Bioinformatics analysis followed by functional genomics demonstrated that AKR1C3 overexpression promotes angiogenesis and aggressiveness of PC-3 cells. These results also suggest that AKR1C3-mediated tumor angiogenesis is regulated by estrogen and androgen metabolism with subsequent IGF-1R and Akt activation followed by VEGF expression in PCa cells.</p

Intent-Recognition-Based Traded Control for Telerobotic Assembly over High-Latency Telemetry

As we deploy robotic manipulation systems into unstructured real-world environments, the tasks which those robots are expected to perform grow very quickly in complexity. These tasks require a greater number of possible actions, more variable environmental conditions, and larger varieties of objects and materials which need to be manipulated. This in turn leads to a greater number of ways in which elements of a task can fail. When the cost of task failure is high, such as in the case of surgery or on-orbit robotic interventions, effective and efficient task recovery is essential. Despite ever-advancing capabilities, however, the current and near future state-of-the-art in fully autonomous robotic manipulation is still insufficient for many tasks in these critical applications. Thus, successful application of robotic manipulation in many application domains still necessitates a human operator to directly teleoperate the robots over some communications infrastructure. However, any such infrastructure always incurs some unavoidable round-trip telemetry latency depending on the distances involved and the type of remote environment. While direct teleoperation is appropriate when a human operator is physically close to the robots being controlled, there are still many applications in which such proximity is infeasible. In applications which require a robot to be far from its human operator, this latency can approach the speed of the relevant task dynamics, and performing the task with direct telemanipulation can become increasingly difficult, if not impossible. For example, round-trip delays for ground-controlled on-orbit robotic manipulation can reach multiple seconds depending on the infrastructure used and the location of the remote robot. The goal of this thesis is to advance the state-of-the art in semi-autonomous telemanipulation under multi-second round-trip communications latency between a human operator and remote robot in order to enable more telerobotic applications. We propose a new intent-recognition-based traded control (IRTC) approach which automatically infers operator intent and executes task elements which the human operator would otherwise be unable to perform. What makes our approach more powerful than the current approaches is that we prioritize preserving the operator's direct manual interaction with the remote environment while only trading control over to an autonomous subsystem when the operator-local intent recognition system automatically determines what the operator is trying to accomplish. This enables operators to perform unstructured and a priori unplanned actions in order to quickly recover from critical task failures. Furthermore, this thesis also describes a methodology for introducing and improving semi-autonomous control in critical applications. Specifically, this thesis reports (1) the demonstration of a prototype system for IRTC-based grasp assistance in the context of transatlantic telemetry delays, (2) the development of a systems framework for IRTC in semi-autonomous telemanipulation, and (3) an evaluation of the usability and efficacy of that framework with an increasingly complex assembly task. The results from our human subjects experiments show that, when incorporated with sufficient lower-level capabilities, IRTC is a promising approach to extend the reach and capabilities of on-orbit telerobotics and future in-space operations

Modular Robot Software Framework for the Intelligent and Flexible Composition of Its Skills

Part 3: Sustainability and Reconfigurability of Manufacturing SystemsInternational audienceCurrent trends such as mass customization necessitate an agile and transformable production. In this context, robotic technologies are seen as a key enabler. But, to date, industrial robots lack the flexibility to easily adapt to changing needs. Therefore, a modular skill-based software framework aiming for free configurability is presented here. A generic task control allows varying incoming tasks to be processed, based on the actual skills of the robot. In this way, the flexible composition of a robot’s skills can be achieved, according to the actual situation

Little Ben: The Ben Franklin Racing Team’s Entry in the 2007 DARPA Urban Challenge

paper describes “Little Ben, ” an autonomous ground vehicle constructed by the Ben Franklin Racing Team for the 2007 DARPA Urban Challenge in under a year and for less than $250,000. The sensing, planning, navigation, and actuation systems for Little Ben were carefully designed to meet the performance demands required of an autonomous vehicle traveling in an uncertain urban environment. We incorporated an array of a global positioning system (GPS)/inertial navigation system, LIDARs, and stereo cameras to provide timely information about the surrounding environment at the appropriate ranges. This sensor information was integrated into a dynamic map that could robustly handle GPS dropouts and errors. Our planning algorithms consisted of a high-level mission planner that used information from the provided route network definition and mission data files to select routes, whereas the lower level planner used the latest dynamic map information to optimize a feasible trajectory to the next waypoint. The vehicle was actuated by a cost-based controller that efficiently handled steering, throttle, and braking maneuvers in both forward and reverse directions. Our software modules were integrated within a hierarchical architecture that allowed rapid development and testing of the system performance. The resulting vehicle was one of six to successfully finish the Urban Challenge

Towards autonomous robotic butlers: Lessons learned with the PR2

Abstract-As autonomous personal robots come of age, we expect certain applications to be executed with a high degree of repeatability and robustness. In order to explore these applications and their challenges, we need tools and strategies that allow us to develop them rapidly. Serving drinks (i.e., locating, fetching, and delivering), is one such application with well-defined environments for operation, requirements for human interfacing, and metrics for successful completion. In this paper we present our experiences and results while building an autonomous robotic assistant using the PR2 1 platform and ROS 2 . The system integrates several new components that are built on top of the PR2&apos;s current capabilities. Perception components include dynamic obstacle identification, mechanisms for identifying the refrigerator, types of drinks, and human faces. Planning components include navigation, arm motion planning with goal and path constraints, and grasping modules. One of the main contributions of this paper is a new task-level executive system, SMACH, based on hierarchical concurrent state machines, which controls the overall behavior of the system. We provide in-depth discussions on the solutions that we found in accomplishing our goal, and the implementation strategies that let us achieve them

ros_control: A generic and simple control framework for ROS

In recent years the Robot Operating System (ROS) has become the 'de facto' standard framework for robotics software development. The `ros_control` framework provides the capability to implement and manage robot controllers with a focus on both _real-time performance_ and _sharing of controllers_ in a robot-agnostic way. The primary motivation for a sepate robot-control framework is the lack of realtime-safe communication layer in ROS. Furthermore, the framework implements solutions for controller-lifecycle and hardware resource management as well as abstractions on hardware interfaces with minimal assumptions on hardware or operating system. The clear, modular design of `ros_control` makes it ideal for both research and industrial use and has indeed seen many such applications to date. The idea of `ros_control` originates from the `pr2_controller_manager` framework specific to the PR2 robot but `ros_control` is fully robot-agnostic. Controllers expose standard ROS interfaces for out-of-the box 3rd party solutions to robotics problems like manipulation path planning (`MoveIt!`) and autonomous navigation (the `ROS navigation stack`). Hence, a robot made up of a mobile base and an arm that support `ros_control` doesn't need any additional code to be written, only a few controller configuration files and it is ready to navigate autonomously and do path planning for the arm. `ros_control` also provides several libraries to support writing custom controllers

A process-based approach to predicting the effect of climate change on the distribution of an invasive allergenic plant in Europe

Ambrosia artemisiifolia is an invasive weed in Europe with highly allergenic pollen. Populations are currently well established and cause significant health problems in the French Rhône valley, Austria, Hungary and Croatia but transient or casual introduced populations are also found in more Northern and Eastern European countries. A process-based model of weed growth, competition and population dynamics was used to predict the future potential for range expansion of A.artemisiifolia under climate change scenarios. The model predicted a northward shift in the available climatic niche for populations to establish and persist, creating a risk of increased health problems in countries including the UK and Denmark. This was accompanied by an increase in relative pollen production at the northern edge of its range. The southern European limit for A.artemisiifolia was not expected to change; populations continued to be limited by drought stress in Spain and Southern Italy. The process-based approach to modelling the impact of climate change on plant populations has the advantage over correlative species distribution models of being able to capture interactions of climate, land use and plant competition at the local scale. However, for this potential to be fully realised, additional empirical data are required on competitive dynamics of A.artemisiifolia in different crops and ruderal plant communities and its capacity to adapt to local conditions